Infection control measures to prevent outbreaks of COVID-19 in Quebec hemodialysis units: a cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Limited space and resources are potential obstacles to infection prevention and control (IPAC) measures in in-centre hemodialysis units. We aimed to assess IPAC measures implemented in Quebec's hemodialysis units during the spring of 2020, describe the characteristics of these units and document the cumulative infection rates during the first year of the COVID-19 pandemic. METHODS: For this cross-sectional survey, we invited leaders from 54 hemodialysis units in Quebec to report information on the physical characteristics of the unit and their perceptions of crowdedness, which IPAC measures were implemented from Mar. 1 to June 30, 2020, and adherence to and feasibility of appropriate IPAC measures. Participating units were contacted again in March 2021 to collect information on the number of COVID-19 cases in order to derive the cumulative infection rate of each unit. RESULTS: Data were obtained from 38 of the 54 units contacted (70% response rate), which provided care to 4485 patients at the time of survey completion. Fourteen units (37%) had implemented appropriate IPAC measures by 3 weeks after Mar. 1, and all 38 units had implemented them by 6 weeks after. One-third of units were perceived as crowded. General measures, masks and screening questionnaires were used in more than 80% of units, and various distancing measures in 55%-71%; reduction in dialysis frequency was rare. Data on cumulative infection rates were obtained from 27 units providing care to 4227 patients. The cumulative infection rate varied from 0% to 50% (median 11.3%, interquartile range 5.2%-20.2%) and was higher than the reported cumulative infection rate in the corresponding region in 23 (85%) of the 27 units. INTERPRETATION: Rates of COVID-19 infection among hemodialysis recipients in Quebec were elevated compared to the general population during the first year of the pandemic, and although hemodialysis units throughout the province implemented appropriate IPAC measures rapidly in the spring of 2020, many units were crowded and could not maintain physical distancing. Future hemodialysis units should be designed to minimize airborne and droplet transmission of infection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".